Abstract Background Technological advances have recently made possible the estimation of maximal oxygen consumption (VO_2max) by consumer wearables. However, the validity of such estimations has not been systematically summarized using meta-analytic methods and there are no standards guiding the validation protocols. Objective The aim was to (1) quantitatively summarize previous studies investigating the validity of the VO_2max estimated by consumer wearables and (2) provide best-practice recommendations for future validation studies. Methods First, we conducted a systematic review and meta-analysis of studies validating the estimation of VO_2max by wearables. Second, based on the state of knowledge (derived from the systematic review) combined with the expert discussion between the members of the Towards Intelligent Health and Well-Being Network of Physical Activity Assessment (INTERLIVE) consortium, we provided a set of best-practice recommendations for validation protocols. Results Fourteen validation studies were included in the systematic review and meta-analysis. Meta-analysis results revealed that wearables using resting condition information in their algorithms significantly overestimated VO_2max (bias 2.17 ml·kg⁻¹·min⁻¹; limits of agreement − 13.07 to 17.41 ml·kg⁻¹·min⁻¹), while devices using exercise-based information in their algorithms showed a lower systematic and random error (bias − 0.09 ml·kg⁻¹·min⁻¹; limits of agreement − 9.92 to 9.74 ml·kg⁻¹·min⁻¹). The INTERLIVE consortium proposed six key domains to be considered for validating wearable devices estimating VO_2max, concerning the following: the target population, reference standard, index measure, testing conditions, data processing, and statistical analysis. Conclusions Our meta-analysis suggests that the estimations of VO_2max by wearables that use exercise-based algorithms provide higher accuracy than those based on resting conditions. The exercise-based estimation seems to be optimal for measuring VO_2max at the population level, yet the estimation error at the individual level is large, and, therefore, for sport/clinical purposes these methods still need improvement. The INTERLIVE network hereby provides best-practice recommendations to be used in future protocols to move towards a more accurate, transparent and comparable validation of VO_2max derived from wearables. PROSPERO ID CRD42021246192.